Inference on inverted exponentiated Rayleigh data from accelerated life testing with hybrid censoring

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dc.contributor.authorYadav, Priya
dc.date.accessioned2026-03-11T09:52:45Z
dc.date.available2026-03-11T09:52:45Z
dc.date.issued2025
dc.description.abstractThis paper addresses the problem of estimating unknown parameters of the inverted exponentiated Rayleigh distribution within the context of accelerated life testing. We consider lifetime data observed through step- stress and type-I hybrid censoring, and incorporate the cumulative expo sure model assumptions to establish connections between the distribu tion at various stress levels. We then write the associated likelihood function based on the observed data and derive maximum likelihood estimators for the distribution’s unknown parameters. Furthermore, employing a Bayesian approach, we initially adopt gamma priors and compute posterior distributions for the parameters. These posterior dis tributions are then utilized to calculate Bayesian estimates using the squared error loss function. To assess the performance of maximum like lihood and Bayesian estimates, we conduct a simulation study under various scenarios, considering both non-informative and informative priors. We also evaluate interval estimates and coverage percentages under both classical and Bayesian approaches. Finally, for illustrative purposes, we analyze two real data sets, demonstrating the practical application of our proposed methodology.
dc.identifier.urihttp://cuh.ndl.gov.in/handle/123456789/1762
dc.language.isoen
dc.titleInference on inverted exponentiated Rayleigh data from accelerated life testing with hybrid censoring
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